Learning Feature Trajectories Using Gabor Filter Bank for Human Activity Segmentation and Recognition. - Sunil Kumar Gupta 001; Y. Senthil Kumar; K. R. Ramakrishnan (ICVGIP, 2008)

Nonnegative shared subspace learning and its application to social media retrieval. - Sunil Kumar Gupta 001; Dinh Q. Phung; Brett Adams; Truyen Tran 001; Svetha Venkatesh (KDD, 2010)

A Bayesian Framework for Learning Shared and Individual Subspaces from Multiple Data Sources. - Sunil Kumar Gupta 001; Dinh Q. Phung; Brett Adams; Svetha Venkatesh (PAKDD (1), 2011)

A nonparametric Bayesian Poisson gamma model for count data. - Sunil Kumar Gupta 001; Dinh Q. Phung; Svetha Venkatesh (ICPR, 2012)

A Bayesian Nonparametric Joint Factor Model for Learning Shared and Individual Subspaces from Multiple Data Sources. - Sunil Kumar Gupta 001; Dinh Quoc Phung; Svetha Venkatesh (SDM, 2012)

A Slice Sampler for Restricted Hierarchical Beta Process with Applications to Shared Subspace Learning. - Sunil Kumar Gupta 001; Dinh Q. Phung; Svetha Venkatesh (UAI, 2012)

Factorial Multi-Task Learning : A Bayesian Nonparametric Approach. - Sunil Kumar Gupta 001; Dinh Q. Phung; Svetha Venkatesh (ICML (3), 2013)

Interactive browsing system for anomaly video surveillance. - Tien-Vu Nguyen; Dinh Q. Phung; Sunil Gupta 001; Svetha Venkatesh (ISSNIP, 2013)

Extraction of latent patterns and contexts from social honest signals using hierarchical Dirichlet processes. - Nguyen Cong Thuong; Dinh Q. Phung; Sunil Gupta 001; Svetha Venkatesh (PerCom, 2013)

Regularized nonnegative shared subspace learning. - Sunil Kumar Gupta 001; Dinh Q. Phung; Brett Adams; Svetha Venkatesh (Data Min. Knowl. Discov., 2013)

Connectivity, Online Social Capital, and Mood: A Bayesian Nonparametric Analysis. - Dinh Q. Phung; Sunil Kumar Gupta 001; Thin Nguyen; Svetha Venkatesh (IEEE Trans. Multim., 2013)

A Bayesian Nonparametric Framework for Activity Recognition Using Accelerometer Data. - Nguyen Cong Thuong; Sunil Gupta 001; Svetha Venkatesh; Dinh Q. Phung (ICPR, 2014)

Intervention-Driven Predictive Framework for Modeling Healthcare Data. - Santu Rana; Sunil Kumar Gupta 001; Dinh Q. Phung; Svetha Venkatesh (PAKDD (1), 2014)

Fixed-lag particle filter for continuous context discovery using Indian Buffet Process. - Nguyen Cong Thuong; Sunil Gupta 001; Svetha Venkatesh; Dinh Q. Phung (PerCom, 2014)

Keeping up with Innovation: A Predictive Framework for Modeling Healthcare Data with Evolving Clinical Interventions. - Sunil Kumar Gupta 001; Santu Rana; Dinh Q. Phung; Svetha Venkatesh (SDM, 2014)

A framework for feature extraction from hospital medical data with applications in risk prediction. - Truyen Tran 001; Wei Luo 001; Dinh Q. Phung; Sunil Gupta 001; Santu Rana; Richard Kennedy; Ann Larkins; Svetha Venkatesh (BMC Bioinform., 2014)

Stable Feature Selection with Support Vector Machines. - Iman Kamkar; Sunil Kumar Gupta 001; Dinh Q. Phung; Svetha Venkatesh (Australasian Conference on Artificial Intelligence, 2015)

Exploiting feature relationships towards stable feature selection. - Iman Kamkar; Sunil Kumar Gupta 001; Dinh Q. Phung; Svetha Venkatesh (DSAA, 2015)

Improved risk predictions via sparse imputation of patient conditions in electronic medical records. - Budhaditya Saha; Sunil Gupta 001; Svetha Venkatesh (DSAA, 2015)

Differentially Private Random Forest with High Utility. - Santu Rana; Sunil Kumar Gupta 001; Svetha Venkatesh (ICDM, 2015)

Collaborating Differently on Different Topics: A Multi-Relational Approach to Multi-Task Learning. - Sunil Kumar Gupta 001; Santu Rana; Dinh Q. Phung; Svetha Venkatesh (PAKDD (1), 2015)

Prediciton of Emergency Events: A Multi-Task Multi-Label Learning Approach. - Budhaditya Saha; Sunil Kumar Gupta 001; Svetha Venkatesh (PAKDD (1), 2015)

What shall I share and with Whom? - A Multi-Task Learning Formulation using Multi-Faceted Task Relationships. - Sunil Gupta 001; Santu Rana; Dinh Q. Phung; Svetha Venkatesh (SDM, 2015)

Stable feature selection for clinical prediction: Exploiting ICD tree structure using Tree-Lasso. - Iman Kamkar; Sunil Kumar Gupta 001; Dinh Q. Phung; Svetha Venkatesh (J. Biomed. Informatics, 2015)

A predictive framework for modeling healthcare data with evolving clinical interventions. - Santu Rana; Sunil Gupta 001; Dinh Q. Phung; Svetha Venkatesh (Stat. Anal. Data Min., 2015)

A Bayesian Nonparametric Approach for Multi-label Classification. - Vu Nguyen 001; Sunil Gupta 001; Santu Rana; Cheng Li 003; Svetha Venkatesh (ACML, 2016)

Understanding Behavioral Differences Between Short and Long-Term Drinking Abstainers from Social Media. - Haripriya Harikumar; Thin Nguyen; Sunil Gupta 001; Santu Rana; Ramachandra Kaimal; Svetha Venkatesh (ADMA, 2016)

Extracting Key Challenges in Achieving Sobriety Through Shared Subspace Learning. - Haripriya Harikumar; Thin Nguyen; Santu Rana; Sunil Gupta 001; Ramachandra Kaimal; Svetha Venkatesh (ADMA, 2016)

Cascade Bayesian Optimization. - Thanh Dai Nguyen; Sunil Gupta 001; Santu Rana; Vu Nguyen 001; Svetha Venkatesh; Kyle J. Deane; Paul G. Sanders (Australasian Conference on Artificial Intelligence, 2016)

Budgeted Batch Bayesian Optimization. - Vu Nguyen 001; Santu Rana; Sunil Kumar Gupta 001; Cheng Li 003; Svetha Venkatesh (ICDM, 2016)

Hyperparameter tuning for big data using Bayesian optimisation. - Tinu Theckel Joy; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (ICPR, 2016)

Stable clinical prediction using graph support vector machines. - Iman Kamkar; Sunil Gupta 001; Cheng Li 003; Dinh Q. Phung; Svetha Venkatesh (ICPR, 2016)

Multiple adverse effects prediction in longitudinal cancer treatment. - Cheng Li 003; Sunil Gupta 001; Santu Rana; Vu Nguyen 001; Svetha Venkatesh; David Ashely; Trish Livingston (ICPR, 2016)

Transfer learning for rare cancer problems via Discriminative Sparse Gaussian Graphical model. - Budhaditya Saha; Sunil Gupta 001; Dinh Q. Phung; Svetha Venkatesh (ICPR, 2016)

Bayesian nonparametric Multiple Instance Regression. - Saravanan Subramanian; Santu Rana; Sunil Gupta 001; Palaniappan Bagavathi Sivakumar; C. Shunmuga Velayutham; Svetha Venkatesh (ICPR, 2016)

Differentially Private Multi-task Learning. - Sunil Kumar Gupta 001; Santu Rana; Svetha Venkatesh (PAISI, 2016)

Flexible Transfer Learning Framework for Bayesian Optimisation. - Tinu Theckel Joy; Santu Rana; Sunil Kumar Gupta 001; Svetha Venkatesh (PAKDD (1), 2016)

Toxicity Prediction in Cancer Using Multiple Instance Learning in a Multi-task Framework. - Cheng Li 003; Sunil Gupta 001; Santu Rana; Wei Luo 001; Svetha Venkatesh; David Ashely; Dinh Q. Phung (PAKDD (1), 2016)

Privacy Aware K-Means Clustering with High Utility. - Thanh Dai Nguyen; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (PAKDD (2), 2016)

Stabilizing l1-norm prediction models by supervised feature grouping. - Iman Kamkar; Sunil Kumar Gupta 001; Dinh Q. Phung; Svetha Venkatesh (J. Biomed. Informatics, 2016)

A new transfer learning framework with application to model-agnostic multi-task learning. - Sunil Gupta 001; Santu Rana; Budhaditya Saha; Dinh Q. Phung; Svetha Venkatesh (Knowl. Inf. Syst., 2016)

Multiple task transfer learning with small sample sizes. - Budhaditya Saha; Sunil Gupta 001; Dinh Q. Phung; Svetha Venkatesh (Knowl. Inf. Syst., 2016)

Modelling multilevel data in multimedia: A hierarchical factor analysis approach. - Sunil Gupta 001; Dinh Q. Phung; Svetha Venkatesh (Multim. Tools Appl., 2016)

Nonparametric discovery of movement patterns from accelerometer signals. - Nguyen Cong Thuong; Sunil Gupta 001; Svetha Venkatesh; Dinh Q. Phung (Pattern Recognit. Lett., 2016)

Regret for Expected Improvement over the Best-Observed Value and Stopping Condition. - Vu Nguyen 001; Sunil Gupta 001; Santu Rana; Cheng Li 003; Svetha Venkatesh (ACML, 2017)

Regret Bounds for Transfer Learning in Bayesian Optimisation. - Alistair Shilton; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (AISTATS, 2017)

Bayesian Optimization in Weakly Specified Search Space. - Vu Nguyen 001; Sunil Gupta 001; Santu Rana; Cheng Li 003; Svetha Venkatesh (ICDM, 2017)

High Dimensional Bayesian Optimization with Elastic Gaussian Process. - Santu Rana; Cheng Li 003; Sunil Gupta 001; Vu Nguyen 001; Svetha Venkatesh (ICML, 2017)

High Dimensional Bayesian Optimization using Dropout. - Cheng Li 003; Sunil Gupta 001; Santu Rana; Vu Nguyen 001; Svetha Venkatesh; Alistair Shilton (IJCAI, 2017)

Process-constrained batch Bayesian optimisation. - Pratibha Vellanki; Santu Rana; Sunil Gupta 001; David Rubin; Alessandra Sutti; Thomas Dorin; Murray Height; Paul G. Sanders; Svetha Venkatesh (NIPS, 2017)

Budgeted Batch Bayesian Optimization With Unknown Batch Sizes. - Vu Nguyen 001; Santu Rana; Sunil Gupta 001; Cheng Li 003; Svetha Venkatesh (CoRR, 2017)

Low overhead octet indexed template security scheme for multi-modal biometric system. - Arvind Selwal; Sunil Kumar Gupta 001; Surender Kumar (J. Intell. Fuzzy Syst., 2017)

Effective sparse imputation of patient conditions in electronic medical records for emergency risk predictions. - Budhaditya Saha; Sunil Gupta 001; Dinh Q. Phung; Svetha Venkatesh (Knowl. Inf. Syst., 2017)

Nonparametric discovery and analysis of learning patterns and autism subgroups from therapeutic data. - Pratibha Vellanki; Thi V. Duong; Sunil Gupta 001; Svetha Venkatesh; Dinh Q. Phung (Knowl. Inf. Syst., 2017)

A Framework for Mixed-Type Multioutcome Prediction With Applications in Healthcare. - Budhaditya Saha; Sunil Gupta 001; Dinh Q. Phung; Svetha Venkatesh (IEEE J. Biomed. Health Informatics, 2017)

Exploiting Strategy-Space Diversity for Batch Bayesian Optimization. - Sunil Gupta 001; Alistair Shilton; Santu Rana; Svetha Venkatesh (AISTATS, 2018)

Sparse Approximation for Gaussian Process with Derivative Observations. - Ang Yang; Cheng Li 003; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (Australasian Conference on Artificial Intelligence, 2018)

Accelerating Experimental Design by Incorporating Experimenter Hunches. - Cheng Li 003; Santu Rana; Sunil Gupta 001; Vu Nguyen 001; Svetha Venkatesh; Alessandra Sutti; David Rubin de Celis Leal; Teo Slezak; Murray Height; Mazher Mohammed; Ian Gibson (ICDM, 2018)

Differentially Private Prescriptive Analytics. - Haripriya Harikumar; Santu Rana; Sunil Gupta 001; Thin Nguyen; Ramachandra Kaimal; Svetha Venkatesh (ICDM, 2018)

Expected Hypervolume Improvement with Constraints. - Majid Abdolshah; Alistair Shilton; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (ICPR, 2018)

Algorithmic Assurance: An Active Approach to Algorithmic Testing using Bayesian Optimisation. - Shivapratap Gopakumar; Sunil Gupta 001; Santu Rana; Vu Nguyen 001; Svetha Venkatesh (NeurIPS, 2018)

Prescriptive Analytics Through Constrained Bayesian Optimization. - Haripriya Harikumar; Santu Rana; Sunil Gupta 001; Thin Nguyen; Ramachandra Kaimal; Svetha Venkatesh (PAKDD (1), 2018)

A Privacy Preserving Bayesian Optimization with High Efficiency. - Thanh Dai Nguyen; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (PAKDD (3), 2018)

Exploration Enhanced Expected Improvement for Bayesian Optimization. - Julian Berk; Vu Nguyen 001; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (ECML/PKDD (2), 2018)

Information-Theoretic Transfer Learning Framework for Bayesian Optimisation. - Anil Ramachandran; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (ECML/PKDD (2), 2018)

Selecting Optimal Source for Transfer Learning in Bayesian Optimisation. - Anil Ramachandran; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (PRICAI (1), 2018)

Efficient Bayesian Optimisation Using Derivative Meta-model. - Ang Yang; Cheng Li 003; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (PRICAI, 2018)

Multi-Target Optimisation via Bayesian Optimisation and Linear Programming. - Alistair Shilton; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (UAI, 2018)

Kernel Pre-Training in Feature Space via m-Kernels. - Alistair Shilton; Sunil Gupta 001; Santu Rana; Pratibha Vellanki; Cheng Li 003; Svetha Venkatesh; Laurence Park 001; Alessandra Sutti; David Rubin; Thomas Dorin; Alireza Vahid; Murray Height; et al. (CoRR, 2018)

Practical Batch Bayesian Optimization for Less Expensive Functions. - Vu Nguyen 001; Sunil Gupta 001; Santu Rana; Cheng Li 003; Svetha Venkatesh (CoRR, 2018)

Hybrid Generative-Discriminative Models for Inverse Materials Design. - Phuoc Nguyen; Truyen Tran 001; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (CoRR, 2018)

Stable Bayesian optimization. - Thanh Dai Nguyen; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (Int. J. Data Sci. Anal., 2018)

Bayesian Functional Optimisation with Shape Prior. - Pratibha Vellanki; Santu Rana; Sunil Gupta 001; David Rubin de Celis Leal; Alessandra Sutti; Murray Height; Svetha Venkatesh (AAAI, 2019)

Bayesian Optimisation for Objective Functions with Varying Smoothness. - A. V. Arun Kumar; Santu Rana; Cheng Li 001; Sunil Gupta 001; Alistair Shilton; Svetha Venkatesh (Australasian Conference on Artificial Intelligence, 2019)

Detection of Compromised Models Using Bayesian Optimization. - Deepthi Praveenlal Kuttichira; Sunil Gupta 001; Dang Nguyen 002; Santu Rana; Svetha Venkatesh (Australasian Conference on Artificial Intelligence, 2019)

Bayesian Optimization with Discrete Variables. - Phuc Luong; Sunil Gupta 001; Dang Nguyen 002; Santu Rana; Svetha Venkatesh (Australasian Conference on Artificial Intelligence, 2019)

Information-Theoretic Multi-task Learning Framework for Bayesian Optimisation. - Anil Ramachandran; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (Australasian Conference on Artificial Intelligence, 2019)

Efficient Bayesian Optimization for Uncertainty Reduction Over Perceived Optima Locations. - Vu Nguyen 001; Sunil Gupta 001; Santu Rana; My T. Thai; Cheng Li 003; Svetha Venkatesh (ICDM, 2019)

Multi-objective Bayesian optimisation with preferences over objectives. - Majid Abdolshah; Alistair Shilton; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (NeurIPS, 2019)

Bayesian Optimization with Unknown Search Space. - Huong Ha 001; Santu Rana; Sunil Gupta 001; Thanh Tang Nguyen; Hung Tran-The; Svetha Venkatesh (NeurIPS, 2019)

Explaining Black-Box Models Using Interpretable Surrogates. - Deepthi Praveenlal Kuttichira; Sunil Gupta 001; Cheng Li 003; Santu Rana; Svetha Venkatesh (PRICAI (1), 2019)

Incomplete Conditional Density Estimation for Fast Materials Discovery. - Phuoc Nguyen; Truyen Tran 001; Sunil Gupta 001; Santu Rana; Matthew Barnett; Svetha Venkatesh (SDM, 2019)

Stable Bayesian Optimisation via Direct Stability Quantification. - Alistair Shilton; Sunil Gupta 001; Santu Rana; Svetha Venkatesh; Majid Abdolshah; Dang Nguyen 002 (CoRR, 2019)

Sparse Spectrum Gaussian Process for Bayesian Optimisation. - Ang Yang; Cheng Li 003; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (CoRR, 2019)

Cost-aware Multi-objective Bayesian optimisation. - Majid Abdolshah; Alistair Shilton; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (CoRR, 2019)

A flexible transfer learning framework for Bayesian optimization with convergence guarantee. - Tinu Theckel Joy; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (Expert Syst. Appl., 2019)

Filtering Bayesian optimization approach in weakly specified search space. - Vu Nguyen 001; Sunil Gupta 001; Santu Rana; Cheng Li 003; Svetha Venkatesh (Knowl. Inf. Syst., 2019)

Bayesian Optimization for Categorical and Category-Specific Continuous Inputs. - Dang Nguyen 002; Sunil Gupta 001; Santu Rana; Alistair Shilton; Svetha Venkatesh (AAAI, 2020)

Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization. - Hung Tran-The; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (AAAI, 2020)

Distributionally Robust Bayesian Quadrature Optimization. - Thanh Tang Nguyen; Sunil Gupta 001; Huong Ha 001; Santu Rana; Svetha Venkatesh (AISTATS, 2020)

Accelerated Bayesian Optimisation through Weight-Prior Tuning. - Alistair Shilton; Sunil Gupta 001; Santu Rana; Pratibha Vellanki; Cheng Li 003; Svetha Venkatesh; Laurence Park 001; Alessandra Sutti; David Rubin; Thomas Dorin; Alireza Vahid; Murray Height; et al. (AISTATS, 2020)

DeepCoDA: personalized interpretability for compositional health data. - Thomas P. Quinn; Dang Nguyen 002; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (ICML, 2020)

Factor Screening using Bayesian Active Learning and Gaussian Process Meta-Modelling. - Cheng Li 003; Santu Rana; Andrew Gill; Dang Nguyen 002; Sunil Gupta 001; Svetha Venkatesh (ICPR, 2020)

Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation. - Julian Berk; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (IJCAI, 2020)

Learning Transferable Domain Priors for Safe Exploration in Reinforcement Learning. - Thommen George Karimpanal; Santu Rana; Sunil Gupta 001; Truyen Tran 001; Svetha Venkatesh (IJCNN, 2020)

Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces. - Hung Tran-The; Sunil Gupta 001; Santu Rana; Huong Ha 001; Svetha Venkatesh (NeurIPS, 2020)

Level Set Estimation with Search Space Warping. - Manisha Senadeera; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (PAKDD (2), 2020)

Scalable Backdoor Detection in Neural Networks. - Haripriya Harikumar; Vuong Le; Santu Rana; Sourangshu Bhattacharya; Sunil Gupta 001; Svetha Venkatesh (ECML/PKDD (2), 2020)

Bayesian Optimization with Missing Inputs. - Phuc Luong; Dang Nguyen 002; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (ECML/PKDD (2), 2020)

Unsupervised Anomaly Detection on Temporal Multiway Data. - Duc Nguyen; Phuoc Nguyen; Kien Do; Santu Rana; Sunil Gupta 001; Truyen Tran 001 (SSCI, 2020)

Bayesian Optimization for Adaptive Experimental Design: A Review. - Stewart Greenhill; Santu Rana; Sunil Gupta 001; Pratibha Vellanki; Svetha Venkatesh (IEEE Access, 2020)

Incorporating Expert Prior Knowledge into Experimental Design via Posterior Sampling. - Cheng Li 003; Sunil Gupta 001; Santu Rana; Vu Nguyen 001; Antonio Robles-Kelly; Svetha Venkatesh (CoRR, 2020)

HyperVAE: A Minimum Description Length Variational Hyper-Encoding Network. - Phuoc Nguyen; Truyen Tran 001; Sunil Gupta 001; Santu Rana; Hieu-Chi Dam; Svetha Venkatesh (CoRR, 2020)

Distributional Reinforcement Learning with Maximum Mean Discrepancy. - Thanh Tang Nguyen; Sunil Gupta 001; Svetha Venkatesh (CoRR, 2020)

Sequential Subspace Search for Functional Bayesian Optimization Incorporating Experimenter Intuition. - Alistair Shilton; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (CoRR, 2020)

Logically Consistent Loss for Visual Question Answering. - Anh-Cat Le-Ngo; Truyen Tran 001; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (CoRR, 2020)

Bayesian optimisation in unknown bounded search domains. - Julian Berk; Sunil Gupta 001; Santu Rana; Vu Nguyen 001; Svetha Venkatesh (Knowl. Based Syst., 2020)

Batch Bayesian optimization using multi-scale search. - Tinu Theckel Joy; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (Knowl. Based Syst., 2020)

Fast hyperparameter tuning using Bayesian optimization with directional derivatives. - Tinu Theckel Joy; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (Knowl. Based Syst., 2020)

Incorporating expert prior in Bayesian optimisation via space warping. - Anil Ramachandran; Sunil Gupta 001; Santu Rana; Cheng Li 003; Svetha Venkatesh (Knowl. Based Syst., 2020)

Bayesian strategy selection identifies optimal solutions to complex problems using an example from GP prescribing. - Steven Allender; Joshua Hayward; Sunil Gupta 001; A. Sanigorski; Santu Rana; Hugh Seward; Stephan Jacobs; Svetha Venkatesh (npj Digit. Medicine, 2020)

High Dimensional Level Set Estimation with Bayesian Neural Network. - Huong Ha 001; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (AAAI, 2021)

Distributional Reinforcement Learning via Moment Matching. - Thanh Nguyen-Tang; Sunil Gupta 001; Svetha Venkatesh (AAAI, 2021)

A New Representation of Successor Features for Transfer across Dissimilar Environments. - Majid Abdolshah; Hung Le 002; Thommen George Karimpanal; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (ICML, 2021)

Bayesian Optimistic Optimisation with Exponentially Decaying Regret. - Hung Tran-The; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (ICML, 2021)

Kernel Functional Optimisation. - Arun Kumar Anjanapura Venkatesh; Alistair Shilton; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (NeurIPS, 2021)

Sparse Spectrum Gaussian Process for Bayesian Optimization. - Ang Yang; Cheng Li 003; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (PAKDD (2), 2021)

Knowledge Distillation with Distribution Mismatch. - Dang Nguyen 002; Sunil Gupta 001; Trong Nguyen; Santu Rana; Phuoc Nguyen; Truyen Tran 001; Ky Le; Shannon Ryan; Svetha Venkatesh (ECML/PKDD (2), 2021)

Variational Hyper-encoding Networks. - Phuoc Nguyen; Truyen Tran 001; Sunil Gupta 001; Santu Rana; Hieu-Chi Dam; Svetha Venkatesh (ECML/PKDD (2), 2021)

Fast Conditional Network Compression Using Bayesian HyperNetworks. - Phuoc Nguyen; Truyen Tran 001; Ky Le; Sunil Gupta 001; Santu Rana; Dang Nguyen 002; Trong Nguyen; Shannon Ryan; Svetha Venkatesh (ECML/PKDD (3), 2021)

Personalized single-cell networks: a framework to predict the response of any gene to any drug for any patient. - Haripriya Harikumar; Thomas P. Quinn; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (BioData Min., 2021)

On Finite-Sample Analysis of Offline Reinforcement Learning with Deep ReLU Networks. - Thanh Nguyen-Tang; Sunil Gupta 001; Hung Tran-The; Svetha Venkatesh (CoRR, 2021)

ALT-MAS: A Data-Efficient Framework for Active Testing of Machine Learning Algorithms. - Huong Ha 001; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (CoRR, 2021)

Combining Online Learning and Offline Learning for Contextual Bandits with Deficient Support. - Hung Tran-The; Sunil Gupta 001; Thanh Nguyen-Tang; Santu Rana; Svetha Venkatesh (CoRR, 2021)

Plug and Play, Model-Based Reinforcement Learning. - Majid Abdolshah; Hung Le 002; Thommen George Karimpanal; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (CoRR, 2021)

A Field Guide to Scientific XAI: Transparent and Interpretable Deep Learning for Bioinformatics Research. - Thomas P. Quinn; Sunil Gupta 001; Svetha Venkatesh; Vuong Le (CoRR, 2021)

Semantic Host-free Trojan Attack. - Haripriya Harikumar; Kien Do; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (CoRR, 2021)

Fairness improvement for black-box classifiers with Gaussian process. - Dang Nguyen 002; Sunil Gupta 001; Santu Rana; Alistair Shilton; Svetha Venkatesh (Inf. Sci., 2021)

Adaptive cost-aware Bayesian optimization. - Phuc Luong; Dang Nguyen 002; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (Knowl. Based Syst., 2021)

An Unified Recurrent Video Object Segmentation Framework for Various Surveillance Environments. - Prashant W. Patil; Akshay Dudhane; Ashutosh Kulkarni; Subrahmanyam Murala; Anil Balaji Gonde; Sunil Gupta 001 (IEEE Trans. Image Process., 2021)

TRF: Learning Kernels with Tuned Random Features. - Alistair Shilton; Sunil Gupta 001; Santu Rana; Arun Kumar Anjanapura Venkatesh; Svetha Venkatesh (AAAI, 2022)

Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization. - Hung Tran-The; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (AISTATS, 2022)

Sympathy-based Reinforcement Learning Agents. - Manisha Senadeera; Thommen George Karimpanal; Sunil Gupta 001; Santu Rana (AAMAS, 2022)

Black-Box Few-Shot Knowledge Distillation. - Dang Nguyen 002; Sunil Gupta 001; Kien Do; Svetha Venkatesh (ECCV (21), 2022)

Video Restoration Framework and Its Meta-adaptations to Data-Poor Conditions. - Prashant W. Patil; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (ECCV (28), 2022)

Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization. - Thanh Nguyen-Tang; Sunil Gupta 001; A. Tuan Nguyen; Svetha Venkatesh (ICLR, 2022)

Semantic Control of Generative Musical Attributes. - Stewart Greenhill; Majid Abdolshah; Vuong Le; Sunil Gupta 001; Svetha Venkatesh (ISMIR, 2022)

Learning to Constrain Policy Optimization with Virtual Trust Region. - Hung Le 002; Thommen Karimpanal George; Majid Abdolshah; Dung Nguyen 001; Kien Do; Sunil Gupta 001; Svetha Venkatesh (NeurIPS, 2022)

Expected Improvement for Contextual Bandits. - Hung Tran-The; Sunil Gupta 001; Santu Rana; Tuan Truong; Long Tran-Thanh; Svetha Venkatesh (NeurIPS, 2022)

Real-Time Skill Discovery in Intelligent Virtual Assistants. - Preeti Gopal; Sunil Gupta 001; Santu Rana; Vuong Le; Trong Nguyen; Svetha Venkatesh (PAKDD (1), 2022)

Memory-Constrained Policy Optimization. - Hung Le 002; Thommen George Karimpanal; Majid Abdolshah; Dung Nguyen 001; Kien Do; Sunil Gupta 001; Svetha Venkatesh (CoRR, 2022)

Defense Against Multi-target Trojan Attacks. - Haripriya Harikumar; Santu Rana; Kien Do; Sunil Gupta 001; Wei Zong; Willy Susilo; Svetha Venkatesh (CoRR, 2022)

Prescriptive analytics with differential privacy. - Haripriya Harikumar; Santu Rana; Sunil Gupta 001; Thin Nguyen; Ramachandra Kaimal; Svetha Venkatesh (Int. J. Data Sci. Anal., 2022)

Verification of integrity of deployed deep learning models using Bayesian Optimization. - Deepthi Praveenlal Kuttichira; Sunil Gupta 001; Dang Nguyen 002; Santu Rana; Svetha Venkatesh (Knowl. Based Syst., 2022)

Dual-frame spatio-temporal feature modulation for video enhancement. - Prashant W. Patil; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (Pattern Recognit., 2022)

On Sample Complexity of Offline Reinforcement Learning with Deep ReLU Networks in Besov Spaces. - Thanh Nguyen-Tang; Sunil Gupta 001; Hung Tran-The; Svetha Venkatesh (Trans. Mach. Learn. Res., 2022)

On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation. - Thanh Nguyen-Tang; Ming Yin; Sunil Gupta 001; Svetha Venkatesh; Raman Arora (AAAI, 2023)

Active Level Set Estimation for Continuous Search Space with Theoretical Guarantee. - Giang Ngo; Dang Nguyen 002; Dat Phan-Trong; Sunil Gupta 001 (ACML, 2023)

Domain Generalization with Interpolation Robustness. - Ragja Palakkadavath; Thanh Nguyen-Tang; Hung Le 002; Svetha Venkatesh; Sunil Gupta 001 (ACML, 2023)

Multi-weather Image Restoration via Domain Translation. - Prashant W. Patil; Sunil Gupta 001; Santu Rana; Svetha Venkatesh; Subrahmanyam Murala (ICCV, 2023)

Gradient Descent in Neural Networks as Sequential Learning in Reproducing Kernel Banach Space. - Alistair Shilton; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (ICML, 2023)

Continual Learning with Dependency Preserving Hypernetworks. - Dupati Srikar Chandra; Sakshi Varshney; P. K. Srijith; Sunil Gupta 001 (WACV, 2023)

Guiding Visual Question Answering with Attention Priors. - Thao Minh Le; Vuong Le; Sunil Gupta 001; Svetha Venkatesh; Truyen Tran 001 (WACV, 2023)

Gradient Descent in Neural Networks as Sequential Learning in RKBS. - Alistair Shilton; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (CoRR, 2023)

Neural-BO: A Black-box Optimization Algorithm using Deep Neural Networks. - Dat Phan-Trong; Hung Tran-The; Sunil Gupta 001 (CoRR, 2023)

BO-Muse: A human expert and AI teaming framework for accelerated experimental design. - Sunil Gupta 001; Alistair Shilton; Arun Kumar A. V.; Shannon Ryan; Majid Abdolshah; Hung Le 002; Santu Rana; Julian Berk; Mahad Rashid; Svetha Venkatesh (CoRR, 2023)

Predictive Modeling through Hyper-Bayesian Optimization. - Manisha Senadeera; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (CoRR, 2023)

Unified Multi-Weather Visibility Restoration. - Ashutosh Kulkarni; Prashant W. Patil; Subrahmanyam Murala; Sunil Gupta 001 (IEEE Trans. Multim., 2023)

NeuralBO: A black-box optimization algorithm using deep neural networks. - Dat Phan-Trong; Hung Tran-The; Sunil Gupta 001 (Neurocomputing, 2023)

Balanced Q-learning: Combining the influence of optimistic and pessimistic targets. - Thommen George Karimpanal; Hung Le 002; Majid Abdolshah; Santu Rana; Sunil Gupta 001; Truyen Tran 001; Svetha Venkatesh (Artif. Intell., 2023)

Root Cause Explanation of Outliers under Noisy Mechanisms. - Phuoc Nguyen; Truyen Tran 001; Sunil Gupta 001; Thin Nguyen; Svetha Venkatesh (AAAI, 2024)

Revisiting Sample Weights Based Method for Noisy-Label Detection and Classification. - Tuan Hoang; Hung Tran; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (ACCV (1), 2024)

Policy Learning for Off-Dynamics RL with Deficient Support. - Linh Le Pham Van; Hung The Tran; Sunil Gupta 001 (AAMAS, 2024)

Generating Realistic Tabular Data with Large Language Models. - Dang Nguyen 002; Sunil Gupta 001; Kien Do; Thin Nguyen; Svetha Venkatesh (ICDM, 2024)

Diversifying Training Pool Predictability for Zero-shot Coordination: A Theory of Mind Approach. - Dung Nguyen 001; Hung Le 002; Kien Do; Sunil Gupta 001; Svetha Venkatesh; Truyen Tran 001 (IJCAI, 2024)

EMOTE: An Explainable Architecture for Modelling the Other through Empathy. - Manisha Senadeera; Thommen Karimpanal George; Stephan Jacobs; Sunil Gupta 001; Santu Rana (IJCAI, 2024)

Active Set Ordering. - Quoc Phong Nguyen; Sunil Gupta 001; Svetha Venkatesh; Bryan Kian Hsiang Low; Patrick Jaillet (NeurIPS, 2024)

Enhanced Bayesian Optimization via Preferential Modeling of Abstract Properties. - A. V. Arun Kumar; Alistair Shilton; Sunil Gupta 001; Santu Rana; Stewart Greenhill; Svetha Venkatesh (ECML/PKDD (6), 2024)

PINN-BO: A Black-Box Optimization Algorithm Using Physics-Informed Neural Networks. - Dat Phan-Trong; Hung The Tran; Alistair Shilton; Sunil Gupta 001 (ECML/PKDD (2), 2024)

Improving Diversity in Black-Box Few-Shot Knowledge Distillation. - Tri-Nhan Vo; Dang Nguyen 002; Kien Do; Sunil Gupta 001 (ECML/PKDD (2), 2024)

Learn to Unlearn for Deep Neural Networks: Minimizing Unlearning Interference with Gradient Projection. - Tuan Hoang; Santu Rana; Sunil Gupta 001; Svetha Venkatesh (WACV, 2024)

Novel Kernel Models and Exact Representor Theory for Neural Networks Beyond the Over-Parameterized Regime. - Alistair Shilton; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (CoRR, 2024)

Robust Transfer Learning for Active Level Set Estimation with Locally Adaptive Gaussian Process Prior. - Giang Ngo; Dang Nguyen 002; Sunil Gupta 001 (CoRR, 2024)

Efficient Symmetry-Aware Materials Generation via Hierarchical Generative Flow Networks. - Tri Minh Nguyen 005; Sherif Abdulkader Tawfik; Truyen Tran 001; Sunil Gupta 001; Santu Rana; Svetha Venkatesh (CoRR, 2024)

Predicting the Reliability of an Image Classifier under Image Distortion. - Dang Nguyen 002; Sunil Gupta 001; Kien Do; Svetha Venkatesh (CoRR, 2024)

High Dimensional Bayesian Optimization using Lasso Variable Selection. - Vu Viet Hoang; Hung The Tran; Sunil Gupta 001; Vu Nguyen 001 (AISTATS, 2025)

Stable Hadamard Memory: Revitalizing Memory-Augmented Agents for Reinforcement Learning. - Hung Le 002; Dung Nguyen 001; Kien Do; Sunil Gupta 001; Svetha Venkatesh (ICLR, 2025)

Causal Discovery via Bayesian Optimization. - Bao Duong; Sunil Gupta 001; Thin Nguyen (ICLR, 2025)

Navigating Social Dilemmas with LLM-based Agents via Consideration of Future Consequences. - Dung Nguyen 001; Hung Le 002; Kien Do; Sunil Gupta 001; Svetha Venkatesh; Truyen Tran 001 (AAMAS, 2025)

Defense Against Multi-target Multi-trigger Backdoor Attacks. - Haripriya Harikumar; Santu Rana; Kien Do; Sunil Gupta 001; Wei Zong; Willy Susilo; Svetha Venkatesh (PAKDD (6), 2025)

Black-box Optimization with Unknown Constraints via Overparameterized Deep Neural Networks. - Dat Phan-Trong; Hung The Tran; Sunil Gupta 001 (UAI, 2025)

EvoCL: Continual Learning over Evolving Domains. - Vishnuprasadh Kumaravelu; P. K. Srijith; Sunil Gupta 001 (WACV, 2025)

Fair Domain Generalization with Heterogeneous Sensitive Attributes Across Domains. - Ragja Palakkadavath; Hung Le 002; Thanh Nguyen-Tang; Sunil Gupta 001; Svetha Venkatesh (WACV, 2025)

Accelerated experimental design using a human-AI teaming framework. - Arun Kumar Anjanapura Venkatesh; Alistair Shilton; Sunil Gupta 001; Shannon Ryan; Majid Abdolshah; Hung Le 002; Santu Rana; Julian Berk; Mahad Rashid; Svetha Venkatesh (Knowl. Based Syst., 2025)

Unpaired recurrent learning for real-world video de-hazing. - Prashant W. Patil; Santosh Nagnath Randive; Sunil Gupta 001; Santu Rana; Svetha Venkatesh; Subrahmanyam Murala (Pattern Recognit., 2025)

Finding the Trigger: Causal Abductive Reasoning on Video Events. - Thao Minh Le; Vuong Le; Kien Do; Sunil Gupta 001; Svetha Venkatesh; Truyen Tran 001 (CoRR, 2025)

Beyond the Known: Decision Making with Counterfactual Reasoning Decision Transformer. - Minh Hoang Nguyen; Linh Le Pham Van; Thommen George Karimpanal; Sunil Gupta 001; Hung Le 002 (CoRR, 2025)

Hybrid Cross-domain Robust Reinforcement Learning. - Linh Le Pham Van; Minh Hoang Nguyen; Hung Le 002; Hung The Tran; Sunil Gupta 001 (CoRR, 2025)

LaGR-SEQ: Language-guided reinforcement learning with sample-efficient querying. - Thommen Karimpanal George; Buddhika Laknath Semage; Santu Rana; Hung Le 002; Truyen Tran 001; Sunil Gupta 001; Svetha Venkatesh (Neural Comput. Appl., 2025)

DmC: Nearest Neighbor Guidance Diffusion Model for Offline Cross-domain Reinforcement Learning. - Linh Le Pham Van; Minh Hoang Nguyen; Duc Kieu; Hung Le 002; Hung The Tran; Sunil Gupta 001 (CoRR, 2025)